RTX PRO 6000 96GB GPU cloud for AI inference, fine-tuning & rendering. OpenAI-compatible APIs. ↓
Delaware, USA
Joined July 2026
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Rent RTX PRO 6000 GPUs for $1.89/GPU-hour.
Sign up and get $1 in free credit.
96GB VRAM per GPU for open-model inference and LoRA fine-tuning. Billed per second.
RTX PRO 6000 GPU rental. 96GB VRAM, from $1.89/GPU-hour, per-second billing. $1 free credit.
ecohash.com/gpu/rtx-pro-6000…
Rent an RTX PRO 6000. 96GB VRAM, from $1.89/GPU-hour. $1 free credit.
ecohash.com/gpu/rtx-pro-6000…
Qwen3.8-27B on one RTX PRO 6000:
1 request: 26.1 output tok/s; 162 ms to first token.
8 concurrent: 179.2 aggregate tok/s; 1.24 s to first token.
Both latencies are P50. Higher throughput comes with a longer wait.
Test conditions + results below.
BF16, vLLM 0.29.0. 1,024 input / 256 output tokens; ~10-minute runs.
Local synthetic tests; internet/gateway latency excluded. Concurrency 8 is a tested load, not a capacity limit.
ecohash.com/models/qwen3.8-2…
Launch an 8-GPU RTX PRO 6000 instance on EcoHash.
8 x 96 GB VRAM and a whole node for your workload. Watch the console walkthrough with narration: containers, SSH, HTTP access, and persistent storage.
Full guide: ecohash.com/blog/launch-eigh…
1.7B parameters. 3.28% WER. 360x real-time.
Qwen3-ASR-1.7B is the smallest of the three speech-to-text models we serve, and it beats the other two on both accuracy and throughput. Measured end-to-end on EcoHash (RTX Pro 6000).
Same endpoint, $0.05 per 1M input tokens.
We ran Qwen-Image-2.1 on a single RTX PRO 6000: 15 fixed-seed prompts, no reruns.
~1 MP: 9.4 s/image, 36.8 GiB peak VRAM
Native 2048²: 52 s, 56.5 GiB
BF16, no quantization or offload
Independent, non-commercial technical evaluation. Method + data:
ecohash.com/blog/qwen-image-…
we just published Qwen-Image-2.1 on RTX PRO 6000: 15-Image Quality and Performance Test medium.com/@ecohash/qwen-ima…
Generated 15 images with Qwen-Image-2.1 on a single NVIDIA RTX PRO 6000.
14 ~1 MP images: 9.378s avg, 36.801 GiB peak.
Native 2048×2048: 52.021s, 56.516 GiB peak.
Prompts + outputs in the replies ↓
ecohash.com/blog/qwen-image-…
14/15 — Prompt
Realistic street-level photo of a minimalist bookstore at blue hour. The illuminated sign reads exactly “微光书店” and “GLOW BOOKS.” Crisp bilingual text, warm shelves visible through glass, softly blurred pedestrians, no other text or logos.
